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authFullName_s : Z. Sakr

Cosmological cluster tension

A. Blanchard , Z. Sakr , S. Ilic
53rd Rencontres de Moriond on Cosmology, Mar 2018, La Thuile, Italy. pp.39-42
Conference papers hal-02411141v1

Euclid: Testing the Copernican principle with next-generation surveys

D. Camarena , V. Marra , Z. Sakr , S. Nesseris , A. da Silva et al.
Astron.Astrophys., 2023, 671, pp.A68
Journal articles hal-03758826v1

Euclid: Forecasts from the void-lensing cross-correlation

M. Bonici , C. Carbone , S. Davini , P. Vielzeuf , L. Paganin et al.
Astron.Astrophys., 2023, 670, pp.A47
Journal articles hal-03737493v1
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Euclid: Impact of non-linear and baryonic feedback prescriptions on cosmological parameter estimation from weak lensing cosmic shear

M. Martinelli , I. Tutusaus , M. Archidiacono , S. Camera , V.F. Cardone et al.
Astron.Astrophys., 2021, 649, pp.A100. ⟨10.1051/0004-6361/202039835⟩
Journal articles hal-02999590v1
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Euclid preparation

A. Blanchard , S. Camera , C. Carbone , V. F. Cardone , S. Casas et al.
Astronomy and Astrophysics - A&A, 2020, 642, pp.A191. ⟨10.1051/0004-6361/202038071⟩
Journal articles hal-02976446v1

Euclid: Forecasts for $k$-cut $3 \times 2$ Point Statistics

P.L. Taylor , T. Kitching , V.F. Cardone , A. Ferté , E.M. Huff et al.
Open J.Astrophys., 2021, 4 (1), pp.6. ⟨10.21105/astro.2012.04672⟩
Journal articles hal-03129526v1

Euclid Preparation XXIX: Forecasts for 10 different higher-order weak lensing statistics

V. Ajani , M. Baldi , A. Barthelemy , A. Boyle , P. Burger et al.
2023
Preprints, Working Papers, ... hal-03986111v1
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Euclid preparation

S. Ilić , N. Aghanim , C. Baccigalupi , J. R. Bermejo-Climent , G. Fabbian et al.
Astronomy and Astrophysics - A&A, 2022, 657, pp.A91. ⟨10.1051/0004-6361/202141556⟩
Journal articles hal-03533670v1
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Euclid preparation

P. Paykari , T. Kitching , H. Hoekstra , R. Azzollini , V. F. Cardone et al.
Astronomy and Astrophysics - A&A, 2020, 635, pp.A139. ⟨10.1051/0004-6361/201936980⟩
Journal articles cea-02516435v1

Euclid preparation. XXX. Evaluating the weak lensing cluster mass biases using the Three Hundred Project hydrodynamical simulations

C. Giocoli , M. Meneghetti , E. Rasia , S. Borgani , G. Despali et al.
2023
Preprints, Working Papers, ... hal-03991062v1

Euclid preparation. XXVII. Covariance model validation for the 2-point correlation function of galaxy clusters

A. Fumagalli , A. Saro , S. Borgani , T. Castro , M. Costanzi et al.
2022
Preprints, Working Papers, ... hal-03892184v1

Testing fundamental cosmological assumptions with Euclid

M. Martinelli , C.J A.P. Martins , S. Nesseris , I. Tutusaus , A. Avgoustidis et al.
17th International Conference on Topics in Astroparticle and Underground Physics, Aug 2021, Valencia, Spain. pp.012019, ⟨10.1088/1742-6596/2156/1/012019⟩
Conference papers hal-03591416v1
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Impact of survey geometry and super-sample covariance on future photometric galaxy surveys

S. Gouyou Beauchamps , F. Lacasa , I. Tutusaus , M. Aubert , P. Baratta et al.
Astron.Astrophys., 2022, 659, pp.A128. ⟨10.1051/0004-6361/202142052⟩
Journal articles hal-03351818v1
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Euclid preparation: XIX. Impact of magnification on photometric galaxy clustering

F. Lepori , I. Tutusaus , C. Viglione , C. Bonvin , S. Camera et al.
Astronomy and Astrophysics - A&A, 2022, 662, pp.A93. ⟨10.1051/0004-6361/202142419⟩
Journal articles hal-03447630v1

Cluster Counts Tension : a Sign of Primordial Non-Gaussianity ?

Z. Sakr , D. Houguenague , A. Blanchard
53rd Rencontres de Moriond on Cosmology, Mar 2018, La Thuile, Italy. pp.43-46
Conference papers hal-03143609v1
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Euclid preparation - XII. Optimizing the photometric sample of the Euclid survey for galaxy clustering and galaxy-galaxy lensing analyses

A. Pocino , I. Tutusaus , F.J. Castander , P. Fosalba , M. Crocce et al.
Astron.Astrophys., 2021, 655, pp.A44. ⟨10.1051/0004-6361/202141061⟩
Journal articles hal-03217522v1
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Euclid: The reduced shear approximation and magnification bias for Stage IV cosmic shear experiments

A. C. Deshpande , T. D. Kitching , V. F. Cardone , P. L. Taylor , S. Casas et al.
Astronomy and Astrophysics - A&A, 2020, 636, pp.A95. ⟨10.1051/0004-6361/201937323⟩
Journal articles cea-02556270v1
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Validating the Fisher approach for stage IV spectroscopic surveys

D. Sapone , S. Yahia-Cherif , I. Tutusaus , A. Blanchard , S. Camera et al.
Astron.Astrophys., 2021, 649, pp.A52. ⟨10.1051/0004-6361/201937312⟩
Journal articles hal-02905949v1
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Euclid: Forecasts from redshift-space distortions and the Alcock-Paczynski test with cosmic voids

N. Hamaus , M. Aubert , A. Pisani , S. Contarini , G. Verza et al.
Astronomy and Astrophysics - A&A, 2022, 658, pp.A20. ⟨10.1051/0004-6361/202142073⟩
Journal articles hal-03426564v1

Euclid preparation XXVI: The Euclid Morphology Challenge. Towards structural parameters for billions of galaxies

H. Bretonnière , U. Kuchner , M. Huertas-Company , E. Merlin , M. Castellano et al.
Astronomy and Astrophysics - A&A, 2023, 671, pp.A102
Journal articles hal-03841727v1

Euclid preparation. XXV. The Euclid Morphology Challenge -- Towards model-fitting photometry for billions of galaxies

E. Merlin , M. Castellano , H. Bretonnière , M. Huertas-Company , U. Kuchner et al.
Astronomy and Astrophysics - A&A, 2023, 671, pp.A101
Journal articles hal-03841758v1

Euclid preparation: XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes and H-band images

L. Bisigello , C. J. Conselice , M. Baes , M. Bolzonella , M. Brescia et al.
2022
Preprints, Working Papers, ... hal-03866380v1

$Euclid$: The importance of galaxy clustering and weak lensing cross-correlations within the photometric $Euclid$ survey

I. Tutusaus , M. Martinelli , V.F. Cardone , S. Camera , S. Yahia-Cherif et al.
Astron.Astrophys., 2020, 643, pp.A70. ⟨10.1051/0004-6361/202038313⟩
Journal articles hal-02634687v1
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Euclid: Constraining dark energy coupled to electromagnetism using astrophysical and laboratory data

M. Martinelli , C.J.A.P. Martins , S. Nesseris , I. Tutusaus , A. Blanchard et al.
Astron.Astrophys., 2021, 654, pp.A148. ⟨10.1051/0004-6361/202141353⟩
Journal articles hal-03248322v1
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Euclid: Forecast constraints on consistency tests of the ΛCDM model

S. Nesseris , D. Sapone , M. Martinelli , D. Camarena , V. Marra et al.
Astron.Astrophys., 2022, 660, pp.A67. ⟨10.1051/0004-6361/202142503⟩
Journal articles hal-03604398v1

Euclid preparation - XX. The Complete Calibration of the Color–Redshift Relation survey: LBT observations and data release

R. Saglia , S. de Nicola , M. Fabricius , V. Guglielmo , J. Snigula et al.
Astron.Astrophys., 2022, 664, pp.A196. ⟨10.1051/0004-6361/202243604⟩
Journal articles hal-03737445v1

Euclid preparation: XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes and H-band images

L. Bisigello , C. J. Conselice , M. Baes , M. Bolzonella , M. Brescia et al.
Monthly Notices of the Royal Astronomical Society: Letters, 2023, 520 (3), pp.3529-3548. ⟨10.1093/mnras/stac3810⟩
Journal articles insu-03947319v1
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Euclid preparation

P. Paykari , T. Kitching , H. Hoekstra , R. Azzollini , V. F. Cardone et al.
Astronomy and Astrophysics - A&A, 2020, 638, pp.C2. ⟨10.1051/0004-6361/201936980e⟩
Journal articles cea-02813362v1

Euclid preparation. XXIV. Calibration of the halo mass function in $\Lambda(\nu)$CDM cosmologies

T. Castro , A. Fumagalli , R.E. Angulo , S. Bocquet , S. Borgani et al.
Astron.Astrophys., 2023, 671, pp.A100
Journal articles hal-03778228v1
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Euclid: Cosmological forecasts from the void size function

S. Contarini , G. Verza , A. Pisani , N. Hamaus , M. Sahlén et al.
Astron.Astrophys., 2022, 667, pp.A162. ⟨10.1051/0004-6361/202244095⟩
Journal articles hal-03691899v1